Journal of the Institute of Electronics and Information Engineers (전자공학회논문지)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Efficient Markov Feature Extraction Method for Image Splicing Detection

접합영상 검출을 위한 효율적인 마코프 특징 추출 방법

  • Han, Jong-Goo (Dept. Electronics Eng., Pusan National University) ;
  • Park, Tae-Hee (Dep. Mechatronics Eng., TongMyung University) ;
  • Eom, Il-Kyu (Dept. Electronics Eng., Pusan National University)
  • 한종구 (부산대학교 전자공학과) ;
  • 박태희 (동명대학교 메카트로닉스공학과) ;
  • 엄일규 (부산대학교 전자공학과)
  • Received : 2014.04.09
  • Accepted : 2014.08.27
  • Published : 2014.09.25
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Abstract

This paper presents an efficient Markov feature extraction method for detecting splicing forged images. The Markov states used in our method are composed of the difference between DCT coefficients in the adjacent blocks. Various first-order Markov state transition probabilities are extracted as features for splicing detection. In addition, we propose a feature reduction algorithm by analysing the distribution of the Markov probability. After training the extracted feature vectors using the SVM classifier, we determine whether the presence of the image splicing forgery. Experimental results verify that the proposed method shows good detection performance with a smaller number of features compared to existing methods.

본 논문에서는 영상접합 조작 검출을 위한 효율적인 마코프 특징을 추출하는 방법을 제안한다. 제안 방법에서 사용하는 마코프 상태는 이산 코사인 변환 영역에서 인접한 블록간 계수의 차이로 구성되며, 블록간 대칭성을 이용하여 다양한 1차 마코프 천이확률을 접합 검출을 위한 특징으로 추출한다. 아울러 마코프 확률의 분포를 분석하여 특징의 수를 줄이는 방법을 제안한다. 추출된 특징 벡터를 SVM(support vector machine) 분류기를 이용하여 학습한 후 영상의 접합 여부를 판별한다. 실험 결과를 통하여 본 논문의 방법이 기존의 방법보다 적은 수의 특징으로 높은 영상접합 조작 결과를 보임을 확인하였다.

Keywords

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